16 citations · 22 across the 23 of their papers we have counts for
8 papers · 1 filter
Learning to Conceal Risk: Controllable Multi-turn Red Teaming for LLMs in the Financial Domain
Gang Cheng, Haibo Jin, Wenbin Zhang +2
Large Language Models (LLMs) are increasingly deployed in finance, where unsafe behavior can lead to serious regulatory risks. However, most red-teaming research focuses on overtly…
GUARD: Guideline Upholding Test through Adaptive Role-play and Jailbreak Diagnostics for LLMs
Haibo Jin, Ruoxi Chen, Peiyan Zhang +3
As Large Language Models (LLMs) become increasingly integral to various domains, their potential to generate harmful responses has prompted significant societal and regulatory conc…
GuardVal: Dynamic Large Language Model Jailbreak Evaluation for Comprehensive Safety Testing
Peiyan Zhang, Haibo Jin, Liying Kang +1
Jailbreak attacks reveal critical vulnerabilities in Large Language Models (LLMs) by causing them to generate harmful or unethical content. Evaluating these threats is particularly…
InfoFlood: Jailbreaking Large Language Models with Information Overload
Advait Yadav, Haibo Jin, Man Luo +2
Large Language Models (LLMs) have demonstrated remarkable capabilities across various domains. However, their potential to generate harmful responses has raised significant societa…
From Hallucinations to Jailbreaks: Rethinking the Vulnerability of Large Foundation Models
Haibo Jin, Peiyan Zhang, Peiran Wang +2
Large foundation models (LFMs) are susceptible to two distinct vulnerabilities: hallucinations and jailbreak attacks. While typically studied in isolation, we observe that defenses…
Reasoning Can Hurt the Inductive Abilities of Large Language Models
Haibo Jin, Peiyan Zhang, Man Luo +1
Large Language Models (LLMs) have shown remarkable progress across domains, yet their ability to perform inductive reasoning - inferring latent rules from sparse examples - remains…
Exploring the Vulnerability of the Content Moderation Guardrail in Large Language Models via Intent Manipulation
Jun Zhuang, Haibo Jin, Ye Zhang +4
Intent detection, a core component of natural language understanding, has considerably evolved as a crucial mechanism in safeguarding large language models (LLMs). While prior work…
Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems
Bang Liu, Xinfeng Li, Jiayi Zhang +45
The advent of large language models (LLMs) has catalyzed a transformative shift in artificial intelligence, paving the way for advanced intelligent agents capable of sophisticated…